{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\Han\Desktop\document\불평등 연구\주제12_부정선거\research and politics\data\4.syntax_robustness_2.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 3 Jul 2024, 00:08:18

{com}. encode country, gen(country_1)

. meologit elecvote subjective_class income high_skilled low_skilled education age sex marital religion urban political_orientation i.year || country:, nolog
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}    36,360
{txt}Group variable: {col 25}{res}country{col 49}{txt}Number of groups{col 67}={res}{col 69}        40

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}       132
{col 63}{txt}avg{col 67}={res}{col 69}     909.0
{col 63}{txt}max{col 67}={res}{col 69}     2,186

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}12{txt}){col 67}={res}{col 70}  1013.93
{txt}Log likelihood = {res}-42993.615{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             elecvote{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      z{col 55}   P>|z|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}subjective_class {c |}{col 23}{res}{space 2}-.0750239{col 35}{space 2} .0064204{col 46}{space 1}  -11.69{col 55}{space 3}0.000{col 63}{space 4}-.0876077{col 76}{space 3}  -.06244
{txt}{space 15}income {c |}{col 23}{res}{space 2}-.0659725{col 35}{space 2} .0098277{col 46}{space 1}   -6.71{col 55}{space 3}0.000{col 63}{space 4}-.0852344{col 76}{space 3}-.0467106
{txt}{space 9}high_skilled {c |}{col 23}{res}{space 2}-.1648053{col 35}{space 2} .0247594{col 46}{space 1}   -6.66{col 55}{space 3}0.000{col 63}{space 4}-.2133328{col 76}{space 3}-.1162777
{txt}{space 10}low_skilled {c |}{col 23}{res}{space 2} .0386219{col 35}{space 2} .0353035{col 46}{space 1}    1.09{col 55}{space 3}0.274{col 63}{space 4}-.0305717{col 76}{space 3} .1078155
{txt}{space 12}education {c |}{col 23}{res}{space 2}-.1407661{col 35}{space 2} .0114646{col 46}{space 1}  -12.28{col 55}{space 3}0.000{col 63}{space 4}-.1632364{col 76}{space 3}-.1182958
{txt}{space 18}age {c |}{col 23}{res}{space 2}-.0663926{col 35}{space 2} .0071103{col 46}{space 1}   -9.34{col 55}{space 3}0.000{col 63}{space 4}-.0803285{col 76}{space 3}-.0524568
{txt}{space 18}sex {c |}{col 23}{res}{space 2}  .239802{col 35}{space 2} .0209178{col 46}{space 1}   11.46{col 55}{space 3}0.000{col 63}{space 4} .1988038{col 76}{space 3} .2808002
{txt}{space 14}marital {c |}{col 23}{res}{space 2}-.1265872{col 35}{space 2} .0215916{col 46}{space 1}   -5.86{col 55}{space 3}0.000{col 63}{space 4}-.1689059{col 76}{space 3}-.0842685
{txt}{space 13}religion {c |}{col 23}{res}{space 2} .0486055{col 35}{space 2} .0256969{col 46}{space 1}    1.89{col 55}{space 3}0.059{col 63}{space 4}-.0017594{col 76}{space 3} .0989705
{txt}{space 16}urban {c |}{col 23}{res}{space 2} .0134007{col 35}{space 2} .0085451{col 46}{space 1}    1.57{col 55}{space 3}0.117{col 63}{space 4}-.0033475{col 76}{space 3} .0301488
{txt}political_orientation {c |}{col 23}{res}{space 2} -.031523{col 35}{space 2} .0124896{col 46}{space 1}   -2.52{col 55}{space 3}0.012{col 63}{space 4}-.0560021{col 76}{space 3}-.0070438
{txt}{space 21} {c |}
{space 17}year {c |}
{space 16}2014  {c |}{col 23}{res}{space 2} .1567711{col 35}{space 2} .0252385{col 46}{space 1}    6.21{col 55}{space 3}0.000{col 63}{space 4} .1073044{col 76}{space 3} .2062377
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}/cut1 {c |}{col 23}{res}{space 2}-1.844667{col 35}{space 2} .1359225{col 46}{space 1}  -13.57{col 55}{space 3}0.000{col 63}{space 4} -2.11107{col 76}{space 3}-1.578264
{txt}{space 16}/cut2 {c |}{col 23}{res}{space 2} .0302468{col 35}{space 2} .1355455{col 46}{space 1}    0.22{col 55}{space 3}0.823{col 63}{space 4}-.2354175{col 76}{space 3}  .295911
{txt}{space 16}/cut3 {c |}{col 23}{res}{space 2} 1.133095{col 35}{space 2}  .135974{col 46}{space 1}    8.33{col 55}{space 3}0.000{col 63}{space 4} .8665906{col 76}{space 3} 1.399599
{txt}{space 16}/cut4 {c |}{col 23}{res}{space 2} 2.451759{col 35}{space 2} .1382763{col 46}{space 1}   17.73{col 55}{space 3}0.000{col 63}{space 4} 2.180743{col 76}{space 3} 2.722776
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}country              {col 23}{c |}
            var(_cons){c |}{col 23}{res}{space 2} .5209546{col 35}{space 2} .1178238{col 63}{space 4} .3344141{col 76}{space 3} .8115499
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 4860.94{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0000

{com}. meologit elecvote high_class income high_skilled low_skilled education age sex marital religion urban political_orientation i.year || country:, nolog
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}    36,360
{txt}Group variable: {col 25}{res}country{col 49}{txt}Number of groups{col 67}={res}{col 69}        40

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}       132
{col 63}{txt}avg{col 67}={res}{col 69}     909.0
{col 63}{txt}max{col 67}={res}{col 69}     2,186

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}12{txt}){col 67}={res}{col 70}   915.24
{txt}Log likelihood = {res}-43043.544{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             elecvote{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      z{col 55}   P>|z|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}high_class {c |}{col 23}{res}{space 2}-.1907147{col 35}{space 2} .0315394{col 46}{space 1}   -6.05{col 55}{space 3}0.000{col 63}{space 4}-.2525308{col 76}{space 3}-.1288987
{txt}{space 15}income {c |}{col 23}{res}{space 2}  -.07831{col 35}{space 2} .0097463{col 46}{space 1}   -8.03{col 55}{space 3}0.000{col 63}{space 4}-.0974124{col 76}{space 3}-.0592075
{txt}{space 9}high_skilled {c |}{col 23}{res}{space 2}-.1768095{col 35}{space 2} .0247225{col 46}{space 1}   -7.15{col 55}{space 3}0.000{col 63}{space 4}-.2252647{col 76}{space 3}-.1283544
{txt}{space 10}low_skilled {c |}{col 23}{res}{space 2} .0586964{col 35}{space 2} .0352404{col 46}{space 1}    1.67{col 55}{space 3}0.096{col 63}{space 4}-.0103736{col 76}{space 3} .1277663
{txt}{space 12}education {c |}{col 23}{res}{space 2}-.1566464{col 35}{space 2} .0113499{col 46}{space 1}  -13.80{col 55}{space 3}0.000{col 63}{space 4}-.1788918{col 76}{space 3} -.134401
{txt}{space 18}age {c |}{col 23}{res}{space 2}-.0636307{col 35}{space 2} .0071033{col 46}{space 1}   -8.96{col 55}{space 3}0.000{col 63}{space 4}-.0775529{col 76}{space 3}-.0497085
{txt}{space 18}sex {c |}{col 23}{res}{space 2}  .235446{col 35}{space 2} .0209092{col 46}{space 1}   11.26{col 55}{space 3}0.000{col 63}{space 4} .1944647{col 76}{space 3} .2764274
{txt}{space 14}marital {c |}{col 23}{res}{space 2}-.1441061{col 35}{space 2}  .021515{col 46}{space 1}   -6.70{col 55}{space 3}0.000{col 63}{space 4}-.1862747{col 76}{space 3}-.1019375
{txt}{space 13}religion {c |}{col 23}{res}{space 2} .0450108{col 35}{space 2} .0256933{col 46}{space 1}    1.75{col 55}{space 3}0.080{col 63}{space 4}-.0053471{col 76}{space 3} .0953687
{txt}{space 16}urban {c |}{col 23}{res}{space 2} .0090225{col 35}{space 2} .0085309{col 46}{space 1}    1.06{col 55}{space 3}0.290{col 63}{space 4}-.0076978{col 76}{space 3} .0257428
{txt}political_orientation {c |}{col 23}{res}{space 2}-.0252773{col 35}{space 2}  .012472{col 46}{space 1}   -2.03{col 55}{space 3}0.043{col 63}{space 4} -.049722{col 76}{space 3}-.0008326
{txt}{space 21} {c |}
{space 17}year {c |}
{space 16}2014  {c |}{col 23}{res}{space 2} .1497452{col 35}{space 2} .0252385{col 46}{space 1}    5.93{col 55}{space 3}0.000{col 63}{space 4} .1002786{col 76}{space 3} .1992118
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}/cut1 {c |}{col 23}{res}{space 2}-1.558048{col 35}{space 2} .1365518{col 46}{space 1}  -11.41{col 55}{space 3}0.000{col 63}{space 4}-1.825684{col 76}{space 3}-1.290411
{txt}{space 16}/cut2 {c |}{col 23}{res}{space 2} .3129501{col 35}{space 2} .1362942{col 46}{space 1}    2.30{col 55}{space 3}0.022{col 63}{space 4} .0458183{col 76}{space 3} .5800819
{txt}{space 16}/cut3 {c |}{col 23}{res}{space 2} 1.413516{col 35}{space 2} .1367692{col 46}{space 1}   10.34{col 55}{space 3}0.000{col 63}{space 4} 1.145453{col 76}{space 3} 1.681579
{txt}{space 16}/cut4 {c |}{col 23}{res}{space 2} 2.730464{col 35}{space 2}  .139091{col 46}{space 1}   19.63{col 55}{space 3}0.000{col 63}{space 4} 2.457851{col 76}{space 3} 3.003078
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}country              {col 23}{c |}
            var(_cons){c |}{col 23}{res}{space 2} .5502833{col 35}{space 2} .1243546{col 63}{space 4} .3533697{col 76}{space 3}  .856926
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 5202.57{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0000

{com}. 
. 
. 
. meologit elecvote low_class income high_skilled low_skilled education age sex marital religion urban political_orientation i.year || country:, nolog
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 67}={res}{col 69}    36,360
{txt}Group variable: {col 25}{res}country{col 49}{txt}Number of groups{col 67}={res}{col 69}        40

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}       132
{col 63}{txt}avg{col 67}={res}{col 69}     909.0
{col 63}{txt}max{col 67}={res}{col 69}     2,186

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}12{txt}){col 67}={res}{col 70}   918.16
{txt}Log likelihood = {res}-43043.399{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             elecvote{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      z{col 55}   P>|z|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}low_class {c |}{col 23}{res}{space 2} .1881968{col 35}{space 2} .0308373{col 46}{space 1}    6.10{col 55}{space 3}0.000{col 63}{space 4} .1277568{col 76}{space 3} .2486367
{txt}{space 15}income {c |}{col 23}{res}{space 2}-.0767406{col 35}{space 2} .0097639{col 46}{space 1}   -7.86{col 55}{space 3}0.000{col 63}{space 4}-.0958775{col 76}{space 3}-.0576037
{txt}{space 9}high_skilled {c |}{col 23}{res}{space 2} -.176011{col 35}{space 2} .0247208{col 46}{space 1}   -7.12{col 55}{space 3}0.000{col 63}{space 4}-.2244628{col 76}{space 3}-.1275592
{txt}{space 10}low_skilled {c |}{col 23}{res}{space 2} .0509384{col 35}{space 2} .0352815{col 46}{space 1}    1.44{col 55}{space 3}0.149{col 63}{space 4}-.0182121{col 76}{space 3} .1200889
{txt}{space 12}education {c |}{col 23}{res}{space 2}-.1549289{col 35}{space 2} .0113725{col 46}{space 1}  -13.62{col 55}{space 3}0.000{col 63}{space 4}-.1772186{col 76}{space 3}-.1326393
{txt}{space 18}age {c |}{col 23}{res}{space 2}-.0658738{col 35}{space 2} .0071099{col 46}{space 1}   -9.27{col 55}{space 3}0.000{col 63}{space 4}-.0798089{col 76}{space 3}-.0519388
{txt}{space 18}sex {c |}{col 23}{res}{space 2} .2380937{col 35}{space 2} .0209102{col 46}{space 1}   11.39{col 55}{space 3}0.000{col 63}{space 4} .1971105{col 76}{space 3} .2790769
{txt}{space 14}marital {c |}{col 23}{res}{space 2}-.1371543{col 35}{space 2} .0215775{col 46}{space 1}   -6.36{col 55}{space 3}0.000{col 63}{space 4}-.1794454{col 76}{space 3}-.0948631
{txt}{space 13}religion {c |}{col 23}{res}{space 2} .0471595{col 35}{space 2} .0256878{col 46}{space 1}    1.84{col 55}{space 3}0.066{col 63}{space 4}-.0031877{col 76}{space 3} .0975067
{txt}{space 16}urban {c |}{col 23}{res}{space 2} .0091147{col 35}{space 2}  .008529{col 46}{space 1}    1.07{col 55}{space 3}0.285{col 63}{space 4}-.0076018{col 76}{space 3} .0258313
{txt}political_orientation {c |}{col 23}{res}{space 2}-.0235621{col 35}{space 2} .0124583{col 46}{space 1}   -1.89{col 55}{space 3}0.059{col 63}{space 4}  -.04798{col 76}{space 3} .0008558
{txt}{space 21} {c |}
{space 17}year {c |}
{space 16}2014  {c |}{col 23}{res}{space 2} .1455012{col 35}{space 2} .0252088{col 46}{space 1}    5.77{col 55}{space 3}0.000{col 63}{space 4}  .096093{col 76}{space 3} .1949095
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}/cut1 {c |}{col 23}{res}{space 2}-1.495187{col 35}{space 2} .1368785{col 46}{space 1}  -10.92{col 55}{space 3}0.000{col 63}{space 4}-1.763464{col 76}{space 3} -1.22691
{txt}{space 16}/cut2 {c |}{col 23}{res}{space 2} .3760114{col 35}{space 2} .1366468{col 46}{space 1}    2.75{col 55}{space 3}0.006{col 63}{space 4} .1081886{col 76}{space 3} .6438342
{txt}{space 16}/cut3 {c |}{col 23}{res}{space 2} 1.477655{col 35}{space 2} .1371408{col 46}{space 1}   10.77{col 55}{space 3}0.000{col 63}{space 4} 1.208864{col 76}{space 3} 1.746447
{txt}{space 16}/cut4 {c |}{col 23}{res}{space 2} 2.795789{col 35}{space 2} .1394736{col 46}{space 1}   20.05{col 55}{space 3}0.000{col 63}{space 4} 2.522426{col 76}{space 3} 3.069152
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}country              {col 23}{c |}
            var(_cons){c |}{col 23}{res}{space 2} .5482042{col 35}{space 2} .1239036{col 63}{space 4}  .352011{col 76}{space 3} .8537457
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit model: {txt}{help j_chibar##|_new:chibar2(01) =}{res} 5175.01{col 55}{txt}Prob >= chibar2 = {res}{col 73}0.0000

{com}. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\Han\Desktop\document\불평등 연구\주제12_부정선거\research and politics\data\4.syntax_robustness_2.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 3 Jul 2024, 00:09:34
{txt}{.-}
{smcl}
{txt}{sf}{ul off}